- qspec.analyze. King.plot ( mode = '' , sigma2d = 1 , scale = None , add_xy = None , add_a = None , font_dict = None , show = True , ** kwargs )[source]
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- Parameters:
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- modestr
The mode of the King-fit. If mode='radii', the x-axis must contain the differences of mean square nuclear charge radii or the Lambda-factor. For every other value, the x-axis is assumed to be an isotope shift such that the slope corresponds to a field-shift ratio F(y_i) / F(x).
- sigma2dint
Whether to draw the actual two-dimensional uncertainty bounds or the classical errorbars. The integer number corresponds to the number of drawn sigma regions.
- scaletuple
Factors to scale the x and the y-axis.
- add_xyarray_like
Additional x and y data to plot. Must have shape (n - 1, k, 5), where n is the dimension of the data vectors, k is the number of additional data points and the five entries in the last axis correspond to arrays of the form [x, x_d, y, y_d, corr_xy].
- add_aarray_like
Additional mass numbers for the additional data. Must have shape (k, 2), where each row is a tuple [A, A_ref].
- font_dictdict
The font_dict passed to matplotlib.rc('font', font_dict).
- showbool
Whether to show the plot.
- kwargsNone
am mode: The mode of the King-fit. If mode='radii', the x-axis must contain the differences of mean square nuclear charge radii or the Lambda-factor. For every other value, the x-axis is assumed to be an isotope shift such that the slope corresponds to a field-shift ratio F(y_i) / F(x).
- Returns:
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- outNone
Generates a King-Plot based on the modified axes 'self.x_mod_nd' and 'self.y_mod_nd' as well as the fit results 'self.results_nd'.